
Data Engineer
1 week ago
Job Description :
What You'll Do :
- ETL Development : Develop and maintain complex ETL/ELT pipelines using Python, AWS Glue Jobs, and PySpark. Utilize PyCharm as your primary development environment.
- Big Data Management : Work extensively with Big Data technologies to process, store, and manage large datasets.
- Virtual Machine Management : Manage and optimize data processing environments on virtual machines, including Google VM instances, AWS EC2 Instances, and Colab.
- Data Quality & Performance : Ensure the high quality, accuracy, and performance of data throughout its lifecycle within the data platform.
- Collaboration : Work closely with data scientists, analysts, and other engineering teams to understand data requirements and deliver robust data solutions.
- Monitoring & Optimization : Monitor data pipelines and systems for performance, reliability, and cost-effectiveness, implementing optimizations as needed.
- Visualization Support (Good to have) : Collaborate with data analysts on data visualization needs, potentially utilizing tools like Looker Studio.
Key Requirements :
- Strong expertise in cloud platforms: AWS S3 and GCP (Google Cloud Platform) are must-haves.
- Proficiency with cloud databases/data warehouses: AWS Redshift/S3, GCP BigQuery, and Big Data technologies are must-haves.
- Mandatory hands-on experience with ETL tools and languages: Python, AWS Glue Jobs, PySpark, and PyCharm.
- Experience working with Virtual Machines such as Colab, Google VM instance, and EC2 Instances is a must have.
- Strong understanding of data modeling, data warehousing, and ETL/ELT to Have :
- Familiarity with other data orchestration tools (e.g., Airflow).
(ref:hirist.tech)-
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